Automated vehicle control and guidance based on real-time blind corner navigational analysis

ABSTRACT

Methods, computer-readable media, systems and apparatuses for determining a blind corner navigational score based on real-time or near real-time navigational analysis using sensor data, digital image data, and a map database are discussed. In some arrangements, detection of a blind sensor may be performing using sensor data, digital image data, and navigational data from a map database system. In at least some arrangements, a warning signal or a vehicle control signal may be transmitted to a vehicle in response to a determination that the blind corner navigational score is above a threshold. In at least some arrangements, route correction and/or route modification based on an upcoming blind corner may be performed if a blind corner navigational score is above a threshold.

This application is a continuation of U.S. patent application Ser. No.15/205,046 filed Jul. 8, 2016, which is incorporated herein by referenceits entirety.

TECHNICAL FIELD

Various aspects of the disclosure relate to data processing systems forautomated vehicle control, guidance, and/or operation based on real-timeor near real-time navigational analysis using sensor data, digital imagedata, and a map database. More specifically, aspects of the disclosurerelate to performing data processing using data from sensors, digitalimagers, and a map database in order to determine an upcoming blindcorner on a navigational route and to perform route correction or routemodification based on the upcoming blind corner.

BACKGROUND

Being aware of hazardous driving conditions can aid in improving thelikelihood of a safe driving experience. However, often drivers rely onnavigational guidance systems that do not alert drivers of upcomingdriving hazards. Although many vehicles include sensing devices todetect changing conditions, those devices may be best suited to evaluatecurrent conditions rather than conditions associated with a road segmentthat a driver is approaching. Accordingly, it may be advantageous todetect upcoming potential dangers and provide adequate warnings todrivers.

SUMMARY

The following presents a simplified summary in order to provide a basicunderstanding of some aspects of the disclosure. The summary is not anextensive overview of the disclosure. It is neither intended to identifykey or critical elements of the disclosure nor to delineate the scope ofthe disclosure. The following summary merely presents some concepts ofthe disclosure in a simplified form as a prelude to the descriptionbelow.

Aspects of the disclosure relate to methods, computer-readable media,systems, and apparatuses for determining a blind corner navigationalscore based on real-time or near real-time navigational analysis usingsensor data, digital image data, and a map database. In somearrangements, the system may be a blind corner navigation system thatincludes at least one processor; and at least one memory storingcomputer-executable instructions that, when executed by the at least oneprocessor, cause the blind corner navigation system to perform blindcorner analysis.

For example, in some arrangements, the system may receive predefinednavigational data from a map database system, process the predefinednavigational data to detect an upcoming blind corner, receive dynamicnavigational data from a digital imaging device, process the dynamicnavigational data to determine a blind corner navigational score, theblind corner navigational score indicating a likelihood that theupcoming blind corner is visible from a vantage point of a vehicle,determine whether the blind corner navigational score is above a firstthreshold, and responsive to a determination that the blind cornernavigational score is above a first threshold, transmitting one or moreof a warning signal or a vehicle control signal to the vehicle. In atleast some arrangements, the digital imaging device may be mounted onthe vehicle. The dynamic navigational data may include one or moredigital images transmitted from the digital imaging device. In oneinstance, processing the dynamic navigational data to determine a blindcorner navigational score may include performing image analysis on theone or more digital images. For example, the predefined navigationaldata may include information indicative of a location of a landmark, andperforming image analysis may include comprises determining whether thelandmark is visible within the one or more digital images.

In at least some arrangements, transmitting the one or more of a warningsignal or a vehicle control signal to the vehicle may includetransmitting a first audio signal to the vehicle responsive todetermining that the blind corner navigational score is above a secondthreshold and transmitting a first vehicle control signal to the vehicleresponsive to determining that the blind corner navigational score isabove a third threshold. The first vehicle control signal may beassociated with a vehicle control event that is adjusted based on aresponse time of the vehicle. The first threshold may be dynamicallymodified based on weather conditions and/or a condition of a road onwhich the vehicle is currently located.

Other features and advantages of the disclosure will be apparent fromthe additional description provided herein.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention and theadvantages thereof may be acquired by referring to the followingdescription in consideration of the accompanying drawings, in which likereference numbers indicate like features, and wherein:

FIG. 1 illustrates computing systems and a network environment that maybe used to implement aspects of the disclosure.

FIG. 2 is an example blind corner navigation system according to one ormore aspects described herein.

FIG. 3 is an example blind corner navigation system environmentillustrating various communications between vehicle-based devices, apersonal mobile device, and blind corner navigation server, according toone or more aspects of the disclosure.

FIG. 4 is a flow diagram illustrating an example method of determining ablind corner navigational score according to one or more aspectsdescribed herein.

FIG. 5A is a block diagram illustrating an example scenario in which ablind corner navigational score may be calculated according to one ormore aspects described herein.

FIG. 5B is a block diagram illustrating an example scenario in which ablind corner navigational score may be calculated according to one ormore aspects described herein

FIG. 6 is a flow diagram illustrating an example method of evaluating apre-planned route for blind corner hazards according to one or moreaspects described herein.

FIGS. 7A and 7B are example user interfaces for providing notificationsto a user according to one or more aspects described herein.

DETAILED DESCRIPTION

In the following description of the various embodiments, reference ismade to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration, various embodiments of thedisclosure that may be practiced. It is to be understood that otherembodiments may be utilized.

As will be appreciated by one of skill in the art upon reading thefollowing disclosure, various aspects described herein may be embodiedas a method, a computer system, or a computer program product.Accordingly, those aspects may take the form of an entirely hardwareembodiment, an entirely software embodiment or an embodiment combiningsoftware and hardware aspects. Furthermore, such aspects may take theform of a computer program product stored by one or more non-transitorycomputer-readable storage media having computer-readable program code,or instructions, embodied in or on the storage media. Any suitablecomputer-readable storage media may be utilized, including hard disks,CD-ROMs, optical storage devices, magnetic storage devices, and/or anycombination thereof. In addition, various signals representing data orevents as described herein may be transferred between a source and adestination in the form of electromagnetic waves traveling throughsignal-conducting media such as metal wires, optical fibers, and/orwireless transmission media (e.g., air and/or space).

FIG. 1 illustrates a block diagram of an example blind corner navigationcomputing device (or system) 101 in a computer system 100 that may beused according to one or more illustrative embodiments of thedisclosure. The blind corner navigation computing device 101 may have aprocessor 103 having circuitry for controlling overall operation of thedevice 101 and its associated components, including RAM 105, ROM 107,input/output module 109, and memory 115. The blind corner navigationcomputing device 101, along with one or more additional devices (e.g.,terminals 141 and 151, security and integration hardware 160) maycorrespond to any of multiple systems or devices described herein, suchas personal mobile devices, vehicle-based computing devices, insurancesystems servers, blind corner navigation servers, internal data sources,external data sources, and other various devices in a blind cornernavigation system. These various computing systems may be configuredindividually or in combination, as described herein, to collect andanalyze driver data, vehicle data (such as sensor data and digitalimaging data), environmental sensor data, and/or driving trip data,detect upcoming blind corners based on the received data, provide audioand/or visual warning signals to a vehicle, provide vehicular controlsto a vehicle, provide modified or corrected route options to a driver,and the like, using the devices of the blind corner navigation systemsdescribed herein. In addition to the features described above, thetechniques described herein also may be used for controlling operationof a vehicle, a vehicle sub-system, and/or a vehicle component,generating and presenting blind corner navigational scores, proposedcorrected routes or modified routes, or the like, to users (e.g., via acomputing device, such as an on-board vehicle computing device, mobiledevice, or the like).

Input/Output (I/O) 109 may include a microphone, keypad, touch screen,and/or stylus through which a user of the blind corner navigationcomputing device 101 may provide input, and may also include one or moreof a speaker for providing audio output and a video display device forproviding textual, audiovisual and/or graphical output. Software may bestored within memory 115 and/or storage to provide instructions toprocessor 103 for enabling device 101 to perform various actions. Forexample, memory 115 may store software used by the device 101, such asan operating system 117, application programs 119, and an associatedinternal database 121. The various hardware memory units in memory 115may include volatile and nonvolatile, removable and non-removable mediaimplemented in any method or technology for storage of information suchas computer-readable instructions, data structures, program modules orother data. Certain devices and systems within blind corner navigationsystems may have minimum hardware requirements in order to supportsufficient storage capacity, processing capacity, analysis capacity,network communication, etc. For instance, in some embodiments, one ormore nonvolatile hardware memory units having a minimum size (e.g., atleast 1 gigabyte (GB), 2 GB, 5 GB, etc.), and/or one or more volatilehardware memory units having a minimum size (e.g., 256 megabytes (MB),512 MB, 1 GB, etc.) may be used in a device 101 (e.g., a personal mobiledevice 101, vehicle-based device 101, blind corner navigation server101, etc.), in order to collect and analyze driver data, vehicle data(such as sensor data and digital imaging data), environmental sensordata, and/or driving trip data, detect upcoming blind corners based onthe received data, provide audio and/or visual warnings to a driver,provide vehicular controls to a vehicle, provide modified or correctedroute options to a driver, etc., using the various devices of the blindcorner navigation systems. Memory 115 also may include one or morephysical persistent memory devices and/or one or more non-persistentmemory devices. Memory 115 may include, but is not limited to, randomaccess memory (RAM) 105, read only memory (ROM) 107, electronicallyerasable programmable read only memory (EEPROM), flash memory or othermemory technology, CD-ROM, digital versatile disks (DVD) or otheroptical disk storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium that canbe used to store the desired information and that can be accessed byprocessor 103.

Processor 103 may include a single central processing unit (CPU), whichmay be a single-core or multi-core processor (e.g., dual-core,quad-core, etc.), or may include multiple CPUs. Processor(s) 103 mayhave various bit sizes (e.g., 16-bit, 32-bit, 64-bit, 96-bit, 128-bit,etc.) and various processor speeds (ranging from 100 MHz to 5 Ghz orfaster). Processor(s) 103 and its associated components may allow thesystem 101 to execute a series of computer-readable instructions, forexample, collect and analyze driver data, vehicle data (such as sensordata and digital imaging data), environmental sensor data, and/ordriving trip data, detect upcoming blind corners based on the receiveddata, provide audio and/or visual warnings to a driver, providevehicular control event signals to a vehicle, provide modified orcorrected route options to a driver, and the like.

The computing device (e.g., a personal mobile device, vehicle-basedsystem, insurance system server, blind corner navigation server, etc.)may operate in a networked environment 100 supporting connections to oneor more remote computers, such as terminals 141, 151, and 161. Suchterminals may be personal computers or servers 141 (e.g., homecomputers, laptops, web servers, database servers), mobile communicationdevices 151 (e.g., mobile phones, tablet computers, etc.), vehicle-basedcomputing systems 161 (e.g., on-board vehicle systems, telematicsdevices, mobile phones or other personal mobile devices withinvehicles), and the like, each of which may include some or all of theelements described above with respect to the blind corner navigationcomputing device 101. The network connections depicted in FIG. 1 includea local area network (LAN) 125 and a wide area network (WAN) 129, and awireless telecommunications network 133, but may also include othernetworks. When used in a LAN networking environment, the computingdevice 101 may be connected to the LAN 125 through a network interfaceor adapter 123. When used in a WAN networking environment, the device101 may include a modem 127 or other means for establishingcommunications over the WAN 129, such as network 131 (e.g., theInternet). When used in a wireless telecommunications network 133, thedevice 101 may include one or more transceivers, digital signalprocessors, and additional circuitry and software for communicating withwireless computing devices 151 and 161 (e.g., mobile phones, portablecustomer computing devices, vehicle-based computing devices and systems,etc.) via one or more network devices 135 (e.g., base transceiverstations) in the wireless network 133.

Also illustrated in FIG. 1 is a security and integration layer 160,through which communications are sent and managed between the device 101(e.g., a personal mobile device, a vehicle-based computing device, ablind corner navigation server, an intermediary server and/or externaldata source servers, etc.) and the remote devices (141, 151, and 161)and remote networks (125, 129, and 133). The security and integrationlayer 160 may comprise one or more separate computing devices, such asweb servers, authentication servers, and/or various networkingcomponents (e.g., firewalls, routers, gateways, load balancers, etc.),having some or all of the elements described above with respect to thecomputing device 101. As an example, a security and integration layer160 of a server 101 may comprise a set of web application serversconfigured to use secure protocols and to insulate the device 101 fromexternal devices 141, 151, and 161. In some cases, the security andintegration layer 160 may correspond to a set of dedicated hardwareand/or software operating at the same physical location and under thecontrol of same entities as device 101. For example, layer 160 maycorrespond to one or more dedicated web servers and network hardware ina vehicle and driver information datacenter or in a cloud infrastructuresupporting cloud-based vehicle identification, vehicle and driver dataretrieval and analysis, sensor data retrieval and analysis, and thelike. In other examples, the security and integration layer 160 maycorrespond to separate hardware and software components which may beoperated at a separate physical location and/or by a separate entity.

As discussed below, the data transferred to and from various devices ina blind corner navigation system 100 may include secure and sensitivedata, such as confidential vehicle operation data, insurance policydata, and confidential user data from drivers and passengers invehicles. Therefore, it may be desirable to protect transmissions ofsuch data by using secure network protocols and encryption, and also toprotect the integrity of the data when stored on the various deviceswithin a system, such as personal mobile devices, vehicle-based devices,insurance servers, blind corner navigation servers, external data sourceservers, or other computing devices in the system 100, by using thesecurity and integration layer 160 to authenticate users and restrictaccess to unknown or unauthorized users. In various implementations,security and integration layer 160 may provide, for example, afile-based integration scheme or a service-based integration scheme fortransmitting data between the various devices in an electronic displaysystem 100. Data may be transmitted through the security and integrationlayer 160, using various network communication protocols. Secure datatransmission protocols and/or encryption may be used in file transfersto protect to integrity of the data, for example, File Transfer Protocol(FTP), Secure File Transfer Protocol (SFTP), and/or Pretty Good Privacy(PGP) encryption. In other examples, one or more web services may beimplemented within the various devices 101 in the system 100 and/or thesecurity and integration layer 160. The web services may be accessed byauthorized external devices and users to support input, extraction, andmanipulation of the data (e.g., vehicle data, driver data, driving tripdata, road segment sensor data, etc.) between the various devices 101 inthe system 100. Web services built to support a personalized displaysystem may be cross-domain and/or cross-platform, and may be built forenterprise use. Such web services may be developed in accordance withvarious web service standards, such as the Web Service Interoperability(WS-I) guidelines. In some examples, a driver data, vehicle data, roadsegment sensor data, and/or driving trip data analysis web service, ablind corner navigation web service, or the like, may be implemented inthe security and integration layer 160 using the Secure Sockets Layer(SSL) or Transport Layer Security (TLS) protocol to provide secureconnections between servers 101 and various clients 141, 151, and 161.SSL or TLS may use HTTP or HTTPS to provide authentication andconfidentiality. In other examples, such web services may be implementedusing the WS-Security standard, which provides for secure SOAP messagesusing XML encryption. In still other examples, the security andintegration layer 160 may include specialized hardware for providingsecure web services. For example, secure network appliances in thesecurity and integration layer 160 may include built-in features such ashardware-accelerated SSL and HTTPS, WS-Security, and firewalls. Suchspecialized hardware may be installed and configured in the security andintegration layer 160 in front of the web servers, so that any externaldevices may communicate directly with the specialized hardware.

Although not shown in FIG. 1, various elements within memory 115 orother components in system 100, may include one or more caches, forexample, CPU caches used by the processing unit 103, page caches used bythe operating system 117, disk caches of a hard drive, and/or databasecaches used to cache content from database 121. For embodimentsincluding a CPU cache, the CPU cache may be used by one or moreprocessors in the processing unit 103 to reduce memory latency andaccess time. In such examples, a processor 103 may retrieve data from orwrite data to the CPU cache rather than reading/writing to memory 115,which may improve the speed of these operations. In some examples, adatabase cache may be created in which certain data from a database 121(e.g., a database of driver data, driving behaviors or characteristics,passenger-related data, vehicle data, driving trip data, road segmentsensor data, etc.) is cached in a separate smaller database on anapplication server separate from the database server (e.g., at apersonal mobile device, vehicle-based data, or intermediary networkdevice or cache device, etc.). For instance, in a multi-tieredapplication, a database cache on an application server can reduce dataretrieval and data manipulation time by not needing to communicate overa network with a back-end database server. These types of caches andothers may be included in various embodiments, and may provide potentialadvantages in certain implementations of blind corner navigationsystems, such as faster response times and less dependence on networkconditions when transmitting and receiving driver information, vehicleinformation, driving trip information, sensor data, digital image data,and the like.

It will be appreciated that the network connections shown areillustrative and other means of establishing a communications linkbetween the computers may be used. The existence of any of variousnetwork protocols such as TCP/IP, Ethernet, FTP, HTTP and the like, andof various wireless communication technologies such as Bluetooth, GSM,CDMA, WiFi, WiMAX, and LTE, is presumed, and the various computingdevices in blind corner navigation system components described hereinmay be configured to communicate using any of these network protocols ortechnologies.

Additionally, one or more application programs 119 may be used by thevarious computing devices 101 within a blind corner navigation system100 (e.g., vehicle data, driver data, road segment sensor data, and/ordriving trip data analysis software applications, blind cornernavigation software applications, etc.), including computer executableinstructions for receiving and analyzing various driver data, vehicledata, environmental sensor data, digital imaging data, and/or drivingtrip data, detecting upcoming blind corners, providing audio and/orvisual warnings to a driver based on a detected upcoming blind corner,providing vehicular control event signals to a vehicle, and/orperforming route correction or modification based on blind corner data.

FIG. 2 is a schematic diagram of an illustrative blind corner navigationsystem 200. The blind corner navigation system 200 may be associatedwith, internal to, operated by, or the like, an entity 201, such as aninsurance provider. In some examples, the entity may be one of variousother types of entities, such as a government entity, corporation orbusiness, university, or the like. Various examples described hereinwill be discussed in the context of an insurance provider. However,nothing in the specification should be viewed as limiting use of thesystems, methods, arrangements, etc. described herein to use only by aninsurance provider.

The blind corner navigation system 200 may include one or more modulesthat may include hardware and/or software configured to perform variousfunctions within the system 200. The one or more modules may beseparate, physical devices or, in other examples, one or more modulesmay be part of the same physical device. A module may include a set ofinstructions stored in a physical memory that are executable by aprocessor (such as processor 103 in FIG. 1) to carry out aspects andfunctions associated with receiving and analyzing various driver data,vehicle data, environmental sensor data, digital imaging data, and/ordriving trip data, detecting upcoming blind corners, providing audioand/or visual warnings to a driver based on a detected upcoming blindcorner, providing vehicular control event signals to a vehicle, and/orperforming route correction or modification based on blind corner data.

The blind corner navigation system 200 may include a blind corneranalysis module 202. The blind corner analysis module 202 may includehardware and/or software configured to receive electronic signals fromone or more sensing devices (such as sensors 216 a, 216 b, 218 a, and218 b) and one or more digital imaging devices (such as digital imager218 a) and determine a blind corner rating for a particular road segmentor driving route. In some arrangements, the blind corner analysis module202 may also receive data from route module 208. Route module 208 mayprovide information associated with a route (or road) on which a vehicleis currently traveling or plans on traveling. In some arrangements, theblind corner analysis module 202 may also receive data from one or moredata stores 204 and 206. The data store may be internal to or associatedwith the entity, such as data store 204, or may be external to theentity, such as data store 206. In some arrangements, the data stores204, 206 may include publicly available information and/or non-publicinformation.

In some examples, data stores 204, 206 may store information related toone or more road segments. A road segment may include a road, portion ofa road, bridge, on-ramp, off-ramp, or any other roadway or portion of aroadway on which vehicles may travel. The data stores 204, 206 mayinclude global positioning system data related to a location of a roadsegment, historical data associated with the road segment (e.g.,accident data, frequency of accidents, severity of accidents, and thelike), a configuration of the road segment (e.g., curved, straight,severe curve, etc.), historic weather data, speed limit data, lightingconditions along the road segment, map data, and the like.

In some arrangements, one or more of data stores 204, 206 may store datarelated to driving behaviors of a user (e.g., received from a telematicsdevice within a vehicle operated by the user, received from a mobiledevice of a user, etc.). One or more of data stores 204, 206 may includevehicle operational data associated with a plurality of vehicles, aswell as insurance information for the plurality of vehicles, accidenthistories, claims data, and the like.

Various other types of data may be stored in one or more of data stores204, 206 without departing from the present disclosure. For instance,one or more of data stores 204, 206 may also store sensor data (e.g.,electronic signals/data) received from one or more sensing devices (suchas sensors 216 a, 216 b and 218 a, 218 b). Sensors 216 a and 216 b maybe vehicle-based sensors that may detect various vehicle operationaldata, as will be discussed more fully herein. Sensors 218 a, 218 b maybe environmental sensors configured to detect conditions along a roadsegment. For instance, the road segment sensors may be arranged along aroad segment (for example, on traffic lights, stop signs, or embeddedwithin or positioned adjacent to the road) and may be configured todetect moisture, temperature, pressure, weight, debris in the roadsegment, potholes or bumps in the road segment, pedestrian traffic,salinity or other road treatment along the road segment (to indicatepossible ice melting), and the like, as will be discussed more fullyherein. Digital imager 220 may be a digital imaging device that maytransmit one or more digital images to dynamic navigational data module210. Digital imager 220 may be a vehicle-mounted digital imaging device,such as a digital camera. Alternatively, digital imager 220 may bemounted along an infrastructure element along a road, such as a barrier,stop sign, traffic light, etc. Data from sensors 216 a, 216 b, 218 a,and 218 b, and from digital imager 220 may be transmitted to, forinstance, dynamic navigational data module 210 for processing, as willbe discussed more fully herein.

The blind corner navigation system 200 may further include a routemodule 208. The route module 208 may receive data related to a currentlocation of a user and a desired destination location of a user. Theroute module 208 may calculate a preliminary route for the user usingmap data from data store 204, 206. Blind corner analysis module 202 mayanalyze the preliminary route using data from data store 204, 206. Blindcorner analysis module 202 may determine a blind corner navigationalscore for the preliminary route. If the blind corner navigational scoreis above a threshold, the route module 208 may generate one or morealternative routes that that may have be relatively less dangerousand/or pose relatively fewer hazards due to blind corners. Thealternative routes may be selected based on historical data and/or basedon real-time or near real-time ratings received from the dynamicnavigational data module 210.

In some examples, the blind corner analysis module 202 may receive oridentify a blind corner navigational score for a road segment on which avehicle is traveling. A blind corner may include an intersection along aroute of travel that is not yet visible from a current vantage point. Ablind corner may also include a curve along the route of travel that isnot yet visible from a current vantage point. The vantage point of avehicle includes the vantage point of a driver of the vehicle as well asthe vantage point of the digital imager. The intersection may be athree-way intersection (e.g., a T-junction, a Y-junction/fork), afour-way intersection (e.g., a crossroads), a five-way intersection, asix-way intersection, and the like. The intersection may not be visiblefrom certain vantage points due to, for example, a curve in the road, afixed or movable obstructions positioned near the intersection (e.g.,plants, buildings, geologic features, other vehicles, etc.), weatherconditions (e.g., rain, snow, fog), lighting conditions (e.g.,darkness), a lack of any landmarks or other signals indicating thepresence of the intersection, and the like. The blind corner analysismodule 202 may receive utilize map data received from data stores 204,206 to identify an upcoming intersection or curve. For example, the mapdata may be stored within a map database system stored in one or more ofdata stores 204, 206. The blind corner analysis module 202 may furtherreceive digital images from digital imager 220, which may be mounted onthe traveling vehicle. The blind corner analysis module 202 may processthe digital images from the vehicle-mounted digital imager 220 todetermine a likelihood that the upcoming intersection or curve isvisible from the vantage point of the traveling vehicle. The likelihoodthat the upcoming intersection or curve is visible from the vantagepoint of the traveling vehicle may be used to calculate a blind cornernavigational score.

If the blind corner navigational score is higher than a threshold,warnings module 214 may trigger one or more audio or visual warnings, asdiscussed in detail below. Additionally, or alternatively, warningsmodule 214 may trigger one or more vehicular control events, asdiscussed in detail below. Triggering the audio/visual warnings and/orthe vehicular control events may include transmitting a warnings signaland/or a vehicular control event signal to a vehicle. In an alternativeembodiment, vehicular control event signals may be transmitted from aseparate module (not shown). In the alternative embodiment, the moduletransmitting the vehicular control event signals may communicate withwarnings module 214 in order to exchange data and/or synchronize (orcoordinate) the transmittal of signals to a vehicle. The audio or visualwarnings and/or the vehicular control events may be adjusted based ondata received from sensors 216 a, 216 b, 218 a, and 218 b and/or datastores 204, 206. In one arrangement, warnings module 214 may useenvironmental data received from environmental sensors 218 a, 218 b toadjust the vehicular control triggers. In another arrangement, warningsmodule 214 may use driver profile data received from data store 204, 206to adjust the audio or visual warnings presented to the driver.Information, such as warnings, vehicular control events, and alternativeroutes, may be provided to users via one or more computing devices. Forinstance, one or more notifications (e.g., of road conditions, alternateroutes, etc.) may be transmitted to a computing device of a user, suchas a smart phone 212 a, personal digital assistant 212 b, tabletcomputing device 212 c, cell phone 212 d, other computing device 212 e,and/or an on-board vehicle computing device 212 f.

In some examples, the sensor data received and/or processed by thesystem may be controlled based on one or more conditions. For instance,although a road segment may have a fixed number of sensors detectingconditions, the system may receive data from a portion of the sensors(e.g., less than all the sensors) when certain conditions are met. Forinstance, if it is daylight, data might be received from less than allsensors on a road segment. If the weather is dry and clear, data may bereceived from less than all the sensors on the road segment.Alternatively, if it is dark and/or the weather conditions are poor,data may be received from all sensors in order to obtain as much data aspossible.

In some examples, receiving data from less than all sensors may includecontrolling sensors transmitting data. For instance, dynamicnavigational data module 210, or other device within the blind cornernavigation system 200 may transmit an indication to one or more sensorsto not transmit data until reactivated. Additionally or alternatively,dynamic navigational data module 210 may filter the data upon receipt.That is, data may be received from all sensors on a road segment butonly data from some sensors may be processed in order to conserveresources (e.g., computing resources), streamline the processing ofdata, improve data processing time, etc. In some examples, adetermination of whether the conditions are sufficient toreceive/process data from fewer than all sensors in a road segment maybe made by the blind corner navigation system (e.g., the dynamicnavigational data module 210 may receive current condition informationand may determine whether conditions meet pre-stored or pre-definedcriteria to receive/process data from less than all sensors).

FIG. 3 is a diagram of an illustrative blind corner navigation system300 including additional aspects not shown in the blind cornernavigation system 200 of FIG. 2 and/or implementing the blind cornernavigation system 200 of FIG. 2. The blind corner navigation system 300includes a vehicle 310, a personal mobile device 330, a blind cornernavigation server 350, a plurality of environmental sensors 318 a and318 b, and additional related components. In an alternative embodiment,the blind corner navigational system may include a navigation deviceinstalled at a vehicle. The navigation device may include a blind corneranalysis computer that may contain some or all of the hardware/softwarecomponents as the computing device 101 depicted in FIG. 1. The blindcorner analysis computer of the navigation device may be configured tostore and analyze driver data, vehicle data, driving data and drivingbehaviors, environmental sensor data, map data, image data, determine anupcoming blind corner, calculate a likelihood that the upcoming blindcorner is visible from a vantage point of a traveling or stationaryvehicle, trigger the transmittal of warning signals and/or controlevents to the vehicle, and the like. As discussed below, the componentsof the system 300, individually or using communication and collaborativeinteraction, may determine upcoming blind corners and, based on digitaldata received from a traveling vehicle, determine a likelihood that theblind corner is visible from the vantage point of the traveling vehicle.To perform such features, aspects of the components shown in FIG. 3 eachmay be implemented in hardware, software, or a combination of the two.Additionally, each component of the system 300 may include a computingdevice (or system) having some or all of the structural componentsdescribed above for computing device 101.

Vehicle 310 in the system 300 may be, for example, an automobile, amotorcycle, a scooter, a bus, a recreational vehicle, a boat, or othervehicle for which vehicle data, location data, driver data (or operatordata), operational data and/or other driving data (e.g., location data,time data, weather data, etc.) may be collected and analyzed. Vehicle310 may include vehicle control computer 317. Vehicle control computer317 may include an on-board vehicle computing device having a displayarranged, for instance, in a dashboard of the vehicle. The vehiclecontrol computer 317 may be connected to or in communication with one ormore systems, sub-systems, or components of the vehicle (e.g., brakingcontrol systems, speed control systems, and the like). In some examplesin which the system anticipates a potential hazard (as discussed below)the vehicle control computer may automatically modify operation of thevehicle and/or transmit one or more signals to one or more systems,sub-systems, or components of the vehicle to modify operation of thevehicle, as discussed herein.

The vehicle 310 includes one or more vehicle operation sensors such asvehicle operation sensor 311 (similar to one or more of sensors 216a-216 b of FIG. 2) capable of detecting and recording various conditionsat the vehicle and operational parameters of the vehicle. For example, avehicle operation sensor may detect and store data corresponding to thevehicle's location (e.g., GPS coordinates), time, travel time, speed anddirection, rates of acceleration or braking, gas mileage, and specificinstances of sudden acceleration, braking, swerving, and distancetraveled. A vehicle operation sensor also may detect and store datareceived from the vehicle's 310 internal systems, such as impact to thebody of the vehicle, air bag deployment, headlights usage, brake lightoperation, door opening and closing, door locking and unlocking, cruisecontrol usage, hazard lights usage, windshield wiper usage, horn usage,turn signal usage, seat belt usage, phone and radio usage within thevehicle, autonomous driving system usage, maintenance performed on thevehicle, and other data collected by the vehicle's computer systems,including the vehicle on-board diagnostic systems (OBD).

Additional vehicle operation sensors may detect and store the externaldriving conditions, for example, external temperature, rain, snow, lightlevels, and sun position for driver visibility. For example, additionalvehicle operation sensors may include external cameras and proximitysensors that detect other nearby vehicles, vehicle spacing, trafficlevels, road conditions, traffic obstructions, animals, cyclists,pedestrians, and other conditions that may factor into a drivingdata/behavior analysis. Additional vehicle operation sensors also maydetect and store data relating to moving violations and the observanceof traffic signals and signs by the vehicle 310. Additional vehicleoperation sensors may detect and store data relating to the maintenanceof the vehicle 310, such as the engine status, oil level, engine coolanttemperature, odometer reading, the level of fuel in the fuel tank,engine revolutions per minute (RPMs), software upgrades, and/or tirepressure.

Vehicle operation sensors also may include cameras and/or proximitysensors capable of recording additional conditions inside or outside ofthe vehicle 310. For example, internal cameras may detect conditionssuch as the number of the passengers and the types of passengers (e.g.adults, children, teenagers, pets, etc.) in the vehicles, and potentialsources of driver distraction within the vehicle (e.g., pets, phoneusage, and unsecured objects in the vehicle). A vehicle operation sensoralso may be configured to collect data identifying a current driver fromamong a number of different possible drivers, for example, based ondriver's seat and mirror positioning, driving times and routes, radiousage, etc. Voice/sound data along with directional data also may beused to determine a seating position within a vehicle 310. A vehicleoperation sensor also may be configured to collect data relating to adriver's movements or the condition of a driver. For example, vehicle310 may include sensors that monitor a driver's movements, such as thedriver's eye position and/or head position, etc. Additional vehicleoperation sensors may collect data regarding the physical or mentalstate of the driver, such as fatigue or intoxication. The condition ofthe driver may be determined through the movements of the driver orthrough other sensors, for example, sensors that detect the content ofalcohol in the air or blood alcohol content of the driver, such as abreathalyzer, along with other biometric sensors.

Certain vehicle operation sensors also may collect information regardingthe driver's route choice, whether the driver follows a given route, andto classify the type of trip (e.g. commute, errand, new route, etc.) andtype of driving (e.g., continuous driving, parking, stop-and-go traffic,etc.). In certain embodiments, vehicle operation sensors may determinewhen and how often the vehicle 310 stays in a single lane or strays intoother lane. A Global Positioning System (GPS), locational sensorspositioned inside the vehicle 310, and/or locational sensors or devicesexternal to the vehicle 310 may be used to determine the route, speed,lane position, road-type (e.g. highway, entrance/exit ramp, residentialarea, etc.) and other vehicle position/location data.

Vehicle operation sensors such as vehicle operation sensor 311 may beinstalled at, on, and/or within the vehicle. For example, a vehicleoperation sensor may be installed with the passenger compartment, theengine compartment, or the trunk of the vehicle. A vehicle operationsensor may also be attached to the exterior or the interior of thevehicle. A vehicle operation sensor may provide sensor data via a wiredor wireless communication interface. For example, a vehicle operationsensor may wirelessly provide sensor data to, e.g., the personal mobiledevice 360 and/or the blind corner navigation server 350. In anotherexample, a vehicle operation sensor may provide sensor data via the OBDport of the vehicle to a data collection device connected to the OBDport. The data collection device may, in turn, provide the sensor datato, e.g., the personal mobile device 360 and/or the blind cornernavigation server 350.

Vehicle 310 may further include digital imager 315. Digital imager 315may comprise a vehicle-mounted digital imaging device, such as a digitalcamera. Alternatively, an optical imaging device or a light detectionand ranging device may be used. Digital imager 315 may be configured totake digital images at preconfigured intervals, or when instructed to doso by vehicle control computer 317. Digital images may include imagesobtained using photographic imaging techniques, videographic imagingtechniques, radar imaging techniques, sonar imaging techniques, andlaser imaging techniques (e.g., LIDAR—Light Detection and Ranging), andother types of imaging techniques suitable for obtaining digital imagesof the route of travel.

The data collected by vehicle operation sensor 311 (as well asenvironmental sensors 318 a and 318 b) and digital imager 315 may bestored and/or analyzed within the vehicle 310, such as for example ablind corner analysis computer 314 integrated into the vehicle, and/ormay be transmitted to one or more external devices. The data collectedby vehicle operation sensor 311 (as well as environmental sensors 318 aand 318 b) and digital imager 315 may be transmitted to telematicsdevice 313 and/or vehicle control computer 317. Telematics device 313may be one or more computing devices containing many or all of thehardware/software components as the computing device 101 depicted inFIG. 1. The telematics device 313 may receive vehicle operation data anddriving data from vehicle operation sensor 311 and image data fromdigital imager 315, and may transmit the data to one or more externalcomputer systems (e.g., personal mobile device 330, blind cornernavigation system 200, blind corner navigation server 350 of aninsurance company, financial institution, or other entity) over awireless transmission network. Telematics device 313 also may beconfigured to detect or determine additional types of data relating toreal-time driving and the condition of the vehicle 310. Telematicsdevice 313 may transmit the additional types of data determined ordetected by telematics device 313 to one or more external computersystems (e.g., personal mobile device 330, blind corner navigationsystem 200, blind corner navigation server 350 of an insurance company,financial institution, or other entity) over a wireless transmissionnetwork. The telematics device 313 also may store the type of vehicle310, for example, the make, model, trim (or sub-model), year, and/orengine specifications, as well as other information such as vehicleowner or driver information, insurance information, and financinginformation for the vehicle 310. Telematics device 313 may transmit thisdata to one or more external computer systems (e.g., personal mobiledevice 330, blind corner navigation system 200, blind corner navigationserver 350 of an insurance company, financial institution, or otherentity) over a wireless transmission network.

As shown in FIG. 3, the data collected by vehicle operation sensor 311and digital imager 315 may be transmitted to blind corner navigationserver 350, personal mobile device 330, and/or additional externalservers and devices via telematics device 313.

In the example shown in FIG. 3, telematics device 313 may receivevehicle driving data from vehicle operation sensor 311 and image datafrom digital imager 315, and may transmit the data to a blind cornernavigation server 350. However, in other examples, one or more of thevehicle operation sensors such as vehicle operation sensor 311 ordigital imager 315 may be configured to receive and transmit datadirectly from or to a blind corner navigation server 350 without using atelematics device. For instance, telematics device 313 may be configuredto receive and transmit data from certain systems or vehicle operationsensors such as vehicle operation sensor 311, while other vehicleoperation sensors or systems may be configured to directly receiveand/or transmit data to a blind corner navigation server 350 withoutusing the telematics device 313. Thus, telematics device 313 may beoptional in certain embodiments.

The system 300 in FIG. 3 also includes a mobile device 330. Mobiledevices 330 may be, for example, smartphones or other mobile phones,personal digital assistants (PDAs), tablet computers, and the like, andmay include some or all of the elements described above with respect tothe computing device 101. As shown in this example, some mobile devicesin systems 300 (e.g., mobile device 330) may be configured to establishcommunication sessions with vehicle-based devices and various internalcomponents of vehicle 310 via wireless networks or wired connections(e.g., for docked devices), whereby such mobile devices 330 may havesecure access to internal vehicle operation sensors, digital imager 315and other vehicle-based systems. However, in other examples, the mobiledevice 330 might not connect to vehicle-based computing devices andinternal components, but may operate independently by communicating withvehicle 310 via their standard communication interfaces (e.g.,telematics device 313, etc.), or might not connect at all to vehicle310.

Mobile device 330 may include a network interface 332, which may includevarious network interface hardware (e.g., adapters, modems, wirelesstransceivers, etc.) and software components to enable mobile device 330to communicate with blind corner navigation server 350, vehicle 310,environmental sensors 318 a and 318 b, and various other externalcomputing devices. One or more specialized software applications, suchas a blind corner analysis application 334 may be stored in the memoryof the mobile device 330. The blind corner analysis application 334 maybe received via network interface 321 from the blind corner navigationserver 350, vehicle 310, or other application providers (e.g.,application stores). As discussed below, the blind corner analysisapplication 334 may or may not include various user interface screens,and may be configured to run as user-initiated applications or asbackground applications. The memory of the mobile device 330 also mayinclude databases configured to receive and store vehicle data, drivingdata, road segment data, map data, digital image data, driving tripdata, and the like, associated with one or more drivers, vehicles,and/or road segments.

Like the vehicle-based computing devices in vehicle 310, mobile device330 also may include various components configured to generate and/orreceive vehicle data, driver data, and driving data or other operationaldata, as well as communicate with environmental sensors 318 a and 318 bto obtain road segment data (such as blind corner data) and/orconditions. For example, using data from the GPS receiver 333, blindcorner analysis application 334 may be able to identify starting andstopping points of driving trips, determine driving speeds, times,routes, and the like. Further using data from the GPS receiver 333,blind corner analysis application 334 may be able to determinepredefined blind corners on a route using received map data and/ordriving data. Additional components of mobile device 330 may be used togenerate or receive driving data for the blind corner analysisapplication 334, such as an accelerometer, compass, and various camerasand proximity sensors. Additional components of the mobile device 330may receive signals or data from road segment sensors and the blindcorner analysis application 334 may use this data to evaluate roadsegment characteristics, conditions, and the like. As discussed herein,the blind corner analysis software application 334 may store and analyzethe data from various mobile device components, road segment sensors,historical data, and the like, and may use this data, in conjunctionwith one or more other devices (e.g., blind corner navigation server350), to determine an upcoming blind corner and to calculate alikelihood that the upcoming blind corner is visible from a vantagepoint of a traveling or stationary vehicle.

When mobile computing devices within vehicles are used to detect vehicledriving data, to receive vehicle driving data from vehicle sensors orimaging devices, and/or to receive data from one or more environmentalsensors, such mobile computing devices 330 may store, analyze, and/ortransmit the data to one or more other devices. For example, mobilecomputing device 330 may transmit data directly to one or more blindcorner navigation servers 350, and thus may be used in conjunction withor instead of telematics devices such as telematics device 313.Moreover, the processing components of the mobile computing device 330may be used to evaluate sensor data to determine upcoming blind spots,processing imaging data, calculate a likelihood that the upcoming blindcorner is visible from a vantage point of a traveling or stationaryvehicle, control sensor data received and/or processed, and performother related functions. Therefore, in certain embodiments, mobilecomputing device 330 may be used in conjunction with, or in place of,the blind corner navigation server 350.

Vehicle 310 may include blind corner analysis computer 314, which may beseparate computing devices or may be integrated into one or more othercomponents within the vehicle 310, such as the telematics device 313,autonomous driving systems, or the internal computing systems of vehicle310. As discussed above, blind corner analysis computers also may beimplemented by computing devices independent from the vehicle 310, suchas mobile computing device 330 of the drivers or passengers, or one ormore separate computer systems (e.g., a user's home or office computer).In any of these examples, the blind corner analysis computer 314 maycontain some or all of the hardware/software components as the computingdevice 101 depicted in FIG. 1. Further, in certain implementations, thefunctionality of the driving analysis computers, such as storing andanalyzing driver data, vehicle data, driving data and driving behaviors,environmental sensor data, map data, image data, determining an upcomingblind corner, calculating a likelihood that the upcoming blind corner isvisible from a vantage point of a traveling or stationary vehicle, andthe like, may be performed in a central blind corner navigation server350 rather than by the individual vehicle 310 or personal mobile device330. In such implementations, the vehicle 310 and and/or mobile device330, might only collect and transmit driver data, sensor data, imagingdata, and the like to blind corner navigation server 350, and thus thevehicle-based blind corner analysis computer 314 may be optional.

The system 300 also may include one or more blind corner navigationservers 350, containing some or all of the hardware/software componentsas the computing device 101 depicted in FIG. 1. The blind cornernavigation server 350 may include hardware, software, and networkcomponents to receive driver data, vehicle data, map data, digitalimaging data, and vehicle operational data/driving data from one or morevehicles 310, mobile devices 330, and other data sources, as well asenvironmental sensor data from one or more environmental sensors 318 aand 318 b, mobile devices 330, and other data sources. The blind cornernavigation server 350 may include a blind corner database 352 and blindcorner navigation analysis system 351 to respectively store and analyzedriver data, vehicle data, map data, digital imaging data, sensor data,and driving data, etc., received from vehicle 310, mobile device 330,environmental sensors 318 a and 318 b, and other data sources. In someexamples, the blind corner navigation analysis system 351 may includemany or all of the components of the blind corner navigation system 200described with respect to FIG. 2.

The blind corner navigation server 350 may initiate communication withand/or retrieve driver data, vehicle data, environmental sensor data,map data, digital imaging data, and driving data from vehicle 310wirelessly via telematics device 313, mobile device 330, or by way ofseparate computing systems over one or more computer networks (e.g., theInternet). Additionally, the blind corner navigation server 350 mayreceive additional data from other third-party data sources, such asexternal traffic databases containing traffic data (e.g., amounts oftraffic, average driving speed, traffic speed distribution, and numbersand types of accidents, etc.) at various times and locations, externalweather databases containing weather data (e.g., rain, snow, sleet, andhail amounts, temperatures, wind, road conditions, visibility, etc.) atvarious times and locations, and other external data sources containingdriving hazard data (e.g., road hazards, traffic accidents, downedtrees, power outages, road construction zones, school zones, and naturaldisasters, etc.), route and navigation information, and insurancecompany databases containing insurance data (e.g., driver score,coverage amount, deductible amount, premium amount, insured status) forthe vehicle, driver, and/or other nearby vehicles and drivers.

Data stored in the road segment database 352 may be organized in any ofseveral different manners. For example, a blind corner table may containdata related to features of the blind corner (such as the location ofthe blind corner), historical accident data for each blind corner,historical rating data for each blind corner, and the like. Other tablesin the database 352 may store additional data, including data typesdiscussed above (e.g. traffic information, road-type and road conditioninformation, weather data, insurance policy data, etc.). Additionally,one or more other databases of other insurance providers containingadditional driver data and vehicle data may be accessed to retrieve suchadditional data.

The blind corner navigation analysis system 351 within the blind cornernavigation server 350 may be configured to retrieve data from thedatabase 352, or may receive driver data, environmental sensor data,vehicle data, map data, digital imaging data, and driving trip directlyfrom vehicle 310, mobile device 330, environmental sensors 318 a and 318b, or other data sources, and may perform blind corner navigationanalyses by determining an upcoming blind corner and calculating alikelihood that the blind corner is visible from the vantage point of aselected vehicle, and other related functions. The functions performedby the blind corner navigation analysis system 351 may be performed byspecialized hardware and/or software separate from the additionalfunctionality of the blind corner navigation server 350. Such functionsmay be similar to those of blind corner analysis module computer 314 ofvehicle 310, and the blind corner analysis application 334 of mobiledevice 330, and further descriptions and examples of the algorithms,functions, and analyses that may be executed by the blind cornernavigation analysis system 351 are described herein.

In various examples, the blind corner analyses and determinations may beperformed entirely in the blind corner navigation server 350, may beperformed entirely in the vehicle-based blind corner analysis computingmodule 314, or may be performed entirely in the blind corner analysisapplication 334 of mobile device 330. In other examples, certainanalyses of driver data, environmental sensor data, map data, digitalimaging data, vehicle data, and driving trip data, may be performed byvehicle-based devices (e.g., within blind corner analysis device 314) ormobile device 330 (e.g., within application 334), while other dataanalyses are performed by the blind corner navigation analysis system351 at the blind corner navigation server 350. For example, avehicle-based blind corner analysis computer 314, or the hardware andsoftware components of mobile device 330 may continuously receive andanalyze driver data, environmental data, map data, vehicle data, drivingtrip data, and the like to detect blind corners so that large amounts ofdata need not be transmitted to the blind corner navigation server 350.Additionally or alternatively, the blind corner navigation server mayreceive data from the environmental sensors 318 a and 318 b, vehiclebased sensors, a vehicle-mounted digital imaging device, and other datasources, and may evaluate blind corners and transmit the outcome to acomputing device of a user. Various other combinations of devicesprocessing data may be used without departing from the invention.

As discussed herein, environmental sensors 318 a and 318 b may includevarious types of sensors. For instance, environmental sensors 318 a and318 b may include sensors to detect temperature, pressure, moisture,road treatments, and the like. The environmental sensors 318 a and 318 bmay be physically placed or embedded in the road segment at variousintervals in order to collect and transmit data to evaluate road segmentconditions. Alternatively, or additionally, environmental sensors 318 aand 318 b may be placed on or within stationary devices within apredefined distance of a road segment, such as a traffic light, stopsign, curb, traffic barricades, and/or safety barriers. Additionally oralternatively, sensors for detecting different conditions may becontained within a single independent housing unit, each with thecapability to detect one or more different conditions (e.g., each sensormay include a temperature sensor, a pressure sensor, etc.).

FIG. 4 is a flow chart illustrating one example method of determining ablind corner navigational score based on received data. The steps shownin the flow chart may be executed by a single computing device, such asvehicle control computer 317, personal mobile device 330, blind cornernavigation system 200, or blind corner navigation server 350.Alternatively, execution of the steps shown in the flow chart may bedistributed between vehicle control computer 317, personal mobile device330, blind corner navigation system 200, and blind corner navigationserver 350. The illustrated method may be performed automatically atregular time intervals (i.e. every 0.5 seconds, every second, every nseconds, etc.), automatically at irregular intervals, or on-demand inresponse to an instruction received from a user. At step 400, predefinednavigational data may be received. Predefined navigational data may bespecific to the current location of a vehicle for which a blind cornernavigational score is being calculated. That is, predefined navigationaldata may be received for specific road segment on which a vehicle istraveling or for a predefined radius around the current location of thevehicle.

Predefined navigational data may include map data. Road information(e.g. road attribute data) in the map data may comprise data about thephysical attributes of the road (e.g., slope, pitch, surface type,grade, number of lanes, traffic signals and signs and the like). In someaspects, the road information may indicate the presence of otherphysical attributes of the road, such as a pothole(s), a slit(s), an oilslick(s), a speed bump(s), an elevation(s) or unevenness (e.g., if onelane of road is higher than the other, which often occurs when road workis being done), etc. In some embodiments, road information may comprisethe physical conditions of the road (e.g., flooded, wet, slick, icy,plowed, not plowed/snow covered, etc.). In some instances, roadinformation may be data from a sensor that gathers and/or analyzes some,most, or all vertical changes in a road. In other examples, roadinformation may include information about characteristics correspondingto the rules of the road or descriptions of the road: posted speedlimit, construction area indicator (e.g., whether location hasconstruction), topography type (e.g., flat, rolling hills, steep hills,etc.), road type (e.g., residential, interstate, 4-lane separatedhighway, city street, country road, parking lot, etc.), road feature(e.g., intersection, gentle curve, blind curve, bridge, tunnel), numberof intersections, whether a roundabout is present, number of railroadcrossings, whether a passing zone is present, whether a merge ispresent, number of lanes, width of roads/lanes, population density,condition of road (e.g., new, worn, severely damaged with sink-holes,severely damaged by erosion, gravel, dirt, paved, etc.), locations ofvarious landmarks that are commonly found near roadways (traffic lights,traffic signs, street signs, safety barriers, traffic barricades, safetybarriers, etc.) wildlife area, state, county, and/or municipality. Insome embodiments, road information may include data about infrastructurefeatures of the road. For example, infrastructure features may includeintersections, bridges, tunnels, railroad crossings, and other roadwayfeatures.

In some aspects, road information may include a large number (e.g., 300)attributes or more for each road segment. Each road may include one ormore road segments, and different roads may include a different numberof road segments. Also, road segments may vary in length. In someembodiments, road segments may be determined based on the attributes.These attributes may be obtained from a database or via a sensor. Insome cases, the attributes of each road segment may be geocoded to aspecific road segment or a specific latitude and longitude. For example,the attributes may be things such as, but not limited to, road geometry,addresses, turn and speed restrictions, physical barriers and gates,one-way streets, restricted access and relative road heights, etc. Asanother example, the road attribute data may consist of informationidentifying that a road segment has a curvature of 6 degrees.

At step 402, the predefined navigational data may be processed todetermine if the vehicle is approaching a blind corner. As noted above,road attribute data may consist of information identifying the curvatureof a road segment. In one arrangement, the curvature may be identifiedusing categorical descriptions, such as “gentle corner,” “blind corner,”“gentle curve,” and/or “blind curve.” In this arrangement, processingthe predefined navigational data may include determining whether anyupcoming corners and/or curves are marked with categorical descriptorsindicating a blind corner or curve. In another arrangement, thecurvature may be identified using a numerical value indicating ameasured curvature (i.e. information identifying that a road segment hasa curvature of 6 degrees). In this arrangement, processing thepredefined navigational data may include determining whether anyupcoming corners and/or curves have a curvature with a numerical valuethat is of a predefined value or within a predefined threshold. Thepredefined value or predefined threshold may be initially determinedbased on one or more factors, such as geographical location of thevehicle, and/or a driving profile of the driver of the vehicle. Thedriving profile may include one or more driving characteristics, such asreaction time (i.e. stop time), average speed, averageacceleration/deceleration, previous reaction times to blind curves, etc.The predefined value/threshold may be dynamically adjusted based on thepredefined navigational data received at step 400. For example, wherethe predefined navigational data indicates that the condition of theroad is hazardous (i.e. the road is flooded, wet, slick, icy, notplowed/snow covered, has a high speed limit, is experiencing hightraffic volume, has a high accident rate, etc.), a first predefinedvalue/threshold may be used. Accordingly, where the predefinednavigational data indicates that the condition of the road is safe (i.e.the road is dry, even, has a low speed limit, has a low accident rate,is experiencing low traffic volume, etc.) a second predefinedvalue/threshold may be used. The first predefined threshold may beindicative of a sharper curve relative to the second predefinedthreshold. In another arrangement, the curvature may be defined in thecontext of a sliding scale. That is, the curvature of a road segment maybe assigned a value on a scale of 1-10, wherein a value of “1” mayindicate a gentle curvature and a value of “10” may indicate a sharpcurvature. The use of a scale of 1-10 is for illustrative purposes, anda similar scale utilizing different numerical values (i.e. 1-5, 1-100)or alphabetical values (A-Z) may be used. In this arrangement,processing the predefined navigational data may include determiningwhether the numerical or alphabetical value assigned to the curvaturerepresents a blind corner.

At step 404, dynamic navigational data may be received. Dynamicnavigational data may include one or more real-time or near real-timeimages produced by a digital imaging device, such as digital imager220/315. The digital imaging device may be mounted on the vehicle forwhich a blind corner navigational score is being calculated.Alternatively, the digital imaging device may be mounted on a secondvehicle that is within a predefined distance of the vehicle for which ablind corner navigational score is being calculated. The images from thedigital imaging device may be received at regular, predefined timeintervals. Alternatively, or additionally, the images from the digitalimaging device may be received in response to a request for imagestransmitted to the digital imaging device.

At step 406, a blind corner navigational score may be calculated. Theblind corner navigational score may be calculated based on thepredefined navigational data and the dynamic navigational data. Theblind corner navigational score may represent a likelihood that theblind corner or curve identified in step 402 is visible from the vantagepoint of a vehicle based on the digital images received in step 404 fromthe digital imaging device mounted on the vehicle. The blind cornernavigational score may be calculated using one or more predefinedmathematical algorithms. The mathematical algorithm may includeimage-analysis algorithms. As noted above in reference to step 400, thepredefined navigational data may include data indicating locations ofvarious landmarks that are commonly found near roadways (traffic lights,traffic signs, street signs, safety barriers, traffic barricades, safetybarriers, etc.) The predefined navigational data may be analyzed toidentify one or more landmarks that are within a predefined vicinity ofthe blind corner detected in step 402. Calculation of the blind cornernavigational score may include performing image analysis on the dynamicnavigational data to determine whether these landmarks are visiblewithin the digital images.

For example, turning to FIG. 5A, vehicle 500 may be traveling on road510. Map data including data characterizing the road 510, road 520, stopsign 540, and bus stop 550 may be received at predefined navigationaldata. Road segment 530 may be identified as a blind corner, and stopsign 540 and bus stop 550 may be identified as landmarks that are withina predefined distance of road segment 530. In this example, one or moredigital images may be received from a digital imager (not shown) mountedon vehicle 500. Calculation of the blind corner navigational score mayinclude analyzing these images to determine if landmarks such as stopsign 540 and/or bus stop 550 are visible within these images. If theselandmarks are not visible within the digital images received fromvehicle 500, there is a low likelihood that blind corner 530 is visiblefrom the vantage point of vehicle 500. Accordingly, the blind cornernavigational score may be assigned a first value. If these landmarks arevisible within the digital images received from vehicle 500, there is ahigh likelihood that blind corner 530 is visible from the vantage pointof vehicle 500. Accordingly, the blind corner navigational score may beassigned a second value. The first value may be higher than a secondvalue. In one arrangement, the blind corner navigational score may beoutput to a user. The blind corner navigational score may be transmittedto a mobile device associated with the user, such as personal mobiledevice 330, or to a vehicle associated with the user, such as vehicle310, or a navigational device associated with the user (not shown).

Alternatively, the system may be configured such that detecting thatlandmarks surrounding a blind corner are visible within digital imagesreceived from the vehicle indicates that the vehicle is approaching theblind corner. That is, in a first scenario, digital images from vehicle500 may indicate that landmarks 540 and 550 are visible from the vantagepoint of vehicle 500. The system may interpret the visibility as anindication that the vehicle 500 is close to the blind corner and assigna relatively high value as the blind corner navigational score. In asecond scenario, digital images from vehicle 500 may indicate thatlandmarks 540 and 550 are not visible from the vantage point of vehicle500. The system may interpret the lack of visibility of the landmarks inthe images as an indicating that the vehicle 500 is still relativelydistant from the blind corner, and thus, that the driver does not yetneed to be warned of the upcoming blind corner. Accordingly, in thissecond scenario, the blind corner navigational score may be assigned arelatively low value. Therefore, in the first scenario, because theblind corner navigational score is assigned a higher score, the blindcorner navigational score is more likely to be above a threshold, thusresulting in warning signals and/or vehicular control event signalsbeing transmitted to vehicle 500. In the second scenario, because theblind corner navigational score is assigned a lower score, the blindcorner navigational score is likely to be below the threshold, thusresulting in no warning signals and/or vehicular control event signalsbeing transmitted to vehicle 500.

Returning to FIG. 4, at step 408, it may be determined whether the blindcorner navigational score is above a threshold value. The thresholdvalue may be predefined, but may additionally be dynamically modifiedbased on the predefined navigational data received at step 400. Forexample, where the predefined navigational data indicates that thecondition of the road segment on which the blind corner is detected ishazardous (i.e. the road is flooded, wet, slick, icy, not plowed/snowcovered, has a high speed limit, is experiencing high traffic volume,has a high accident rate, etc.), a first predefined value/threshold maybe used. Accordingly, where the predefined navigational data indicatesthat the condition of the road segment on which the blind corner isdetected is safe (i.e. the road is dry, even, has a low speed limit, hasa low accident rate, is experiencing low traffic volume, etc.) a secondpredefined value/threshold may be used. The first predefined thresholdmay be lower than the second predefined threshold.

If, at step 408, it is determined that the blind corner navigationalscore is not greater than the threshold, processing may return to step400. If, at step 408, it is determined that the blind cornernavigational score is greater than the threshold, one or more blindcorner warnings and/or blind corner corrective events may be triggeredat step 412. Triggering the audio/visual warnings and/or the vehicularcontrol events may include transmitting a warnings signal and/or avehicular control event signal to the vehicle. Drivers may be givenblind corner warnings via audio, visual, and/or tactile feedback. Thesemay include, but are not limited to, an audio message, a video message,an audio alarm/beeping, flashing of lights within a car,flashing/lighting one or more LED alarm lights, vibrating the steeringwheel, and the like. The blind corner navigational score may determinethe set of warnings to be outputted. For example, one or more LEDs mayflash a blue light if the blind corner navigational score is above afirst threshold, and may flash a red light if the blind cornernavigational score is above a second threshold, where the firstthreshold is lower than the second threshold. In another example, theintensity of the vibration of the steering wheel may be related to thevalue of the blind corner navigational score (that is, a first value ofa blind corner navigational score results in a first intensity ofvibration and a second value of a blind corner navigational scoreresults in a second intensity of vibration, wherein the second value andsecond intensity are higher than the first level and first intensity,respectively).

The audio warning, which may be in the form of an audio message, may betransmitted to one or more components of a vehicle (such as vehiclecontrol computer 317) or to one or more devices within a vehicle (suchas personal mobile device 330). Vehicle control computer 317 may thenoutput the audio message via one or more audio devices associated withthe vehicle. Similarly, personal mobile device 330 may output the audiomessage via one or more audio devices associated with the personalmobile device 330.

The video warning, which may include an audio message, may betransmitted to one or more components of a vehicle (such as vehiclecontrol computer 317) or to one or more devices within a vehicle (suchas personal mobile device 330). The video warning may include one ormore textual/graphical elements indicating that the vehicle isapproaching a blind corner. In one arrangement, the video warning mayinclude an audio warning. Vehicle control computer 317 may then outputthe video message on the interior of the vehicle (e.g., on a displayscreen of a navigational device, LCD screen, LED screen, plasma screen,and the like), or on the windshield of the vehicle (e.g., heads-updisplay [HUD]). In some embodiments, vehicle control computer 317 maydisplay the video message as a hologram, or on augmented reality (AR)glasses, or the like. Personal mobile device 330 may display the videomessage on a display screen of personal mobile device 330.

Any of the audio, visual, and/or tactile warnings may be customizedbased on user-settings. That is, a first driver of a first vehicle mayconfigure the warnings such that only audio warnings are sent to thefirst vehicle. A second driver of a second vehicle may configure theblind corner warnings such that only video warnings and tactile warningsare sent to the second vehicle or a mobile computing device associatedwith the second driver. The first driver may further configure the blindcorner warnings such that warnings are only sent to the first vehicle ifthe blind corner navigational score is above a first threshold. Thesecond driver may further configure the blind corner warnings such thatwarnings are only sent to the second vehicle if the blind cornernavigational score is above a second threshold. The first threshold maybe the same as, higher than, or lower than the second threshold.

Additionally, any of the audio, visual, and/or tactile warnings may becustomized based on the user characteristics of the driver. In onearrangement, driver profile data may be retrieved from data store 204,206 and used as the basis for adjusting the transmittal of a warningsignal. Driver profile data may include the driver's age, a quality ofthe driver's eye-sight, estimated reaction time, routes commonly drivenby the driver, the number of blind corners on the driver's commonroutes, etc. In another arrangement, driver profile data, such as thereaction time of the driver, may have been previously determined or maybe dynamically determined by one or more computing devices, such asblind corner navigation system 200 or blind corner navigation server350. As discussed above, sensor data (including proximity data) anddigital imaging data may be received from a traveling vehicle.

To determine the reaction time of a driver, blind corner navigationsystem 200, or blind corner navigation server 350 may analyze andmeasure the image and/or proximity data. For example, image and/orproximity data may show that a vehicle swerved to avoid hitting anobject that was in the vehicle's path (e.g., a pedestrian, cyclist,animal, disabled vehicle, etc.). Blind corner navigation system 200 orblind corner navigation server 350 may analyze the image and/orproximity data to determine the distance between the object and thevehicle when the object entered the vehicle's path, or the distance atwhich the object was first visible to the driver of the vehicle. Fromthis distance, blind corner navigation system 200 or blind cornernavigation server 350 may use the vehicle's speed to calculate theamount of time that the driver had to react to the obstruction, and maycompare that amount of time to the amount of time that the driver tookto react to the observation. For instance, if the driver had a fewseconds to react to the obstruction (e.g., 0-3 seconds), and the driverreacted to the obstruction within that time frame, the blind cornernavigation system 200 or the blind corner navigation server 350 maydetermine that the driver has a relatively quick reaction time. On theother hand, if the driver had ample time (e.g., 5-10 seconds) to observeand avoid the obstruction, but only swerved at the last second, blindcorner navigation system 200 or blind corner navigation server 350 maydetermine that the driver has a relatively slow reaction time. Blindcorner navigation system 200 or blind corner navigation server 350 maystore a driver's reaction time data in a user profile that may later beaccessed when performing blind corner analysis.

Alternatively, the blind corner navigation system 200 may be configuredto test the reaction time of a driver before the driver operates thevehicle and store a baseline reaction time for the driver as a type ofdriver profile data in the driver profile. For example, while thevehicle is in an inoperative state (e.g., parked and/or not running),the blind corner navigation system 200 may initiate a reaction time testin which the driver is instructed to apply the brakes when presentedwith a notification. The notification may be a visible notification(e.g., presented at a dashboard display within the vehicle) and/or anaudible notification (e.g., presented using the audio system of thevehicle). The blind corner navigation system 200 may then present thenotification random amount of time following initiation of the test (soas to be unexpected to the driver), and measure the duration betweenpresentation of the notification and application of the brakes. Theblind corner navigation system 200 may repeat the test one or more timesand set the baseline reaction time of the driver profile to the averageof multiple test results. The blind corner navigation system 200 may beconfigured to measure the reaction time of the driver at different timesof the day, e.g., in the morning when the driver might be expected to berested and thus more alert and at night when the driver might beexpected to be tired and thus less alert. The driver profile may thusalso include a reaction time offset that is used to adjust the baselinereaction time depending on the time of day during which the driver isoperating the vehicle.

The driver profile data retrieved from data store 204, 206 and/orcalculated by the blind corner navigation system 200 or the blind cornernavigation server 350 may be used to configure the timing of the warningsignals or the type of warnings output to the driver. For example, thewarnings may be transmitted relatively sooner for younger drivers (e.g.,teenagers), elderly drivers, and less experienced drivers (e.g., driverswith less than x number of years driving experience). In anotherexample, the warnings may be transmitted relatively sooner for driverswith relatively slow reaction times. In another example, the audio levelof a warning may be set to be relatively high for younger drivers (e.g.,teenagers), elderly drivers, less experienced drivers (e.g., driverswith less than x number of years driving experience) and drivers withrelatively slow reaction times.

The blind corner corrective events triggered at step 412 may include oneor more control events for a vehicle. The one or more control events forthe vehicle may be sent to a computing device associated with thevehicle, such as vehicle control computer 317. Vehicle control computer317 may then execute the control events by controlling the appropriatedevice or by forwarding the received control event to the appropriatecontrol device. In one arrangement, a blind corner corrective event mayinclude a pre-tensioning of one or more seat belts in the vehicle. Inthis arrangement, the blind corner corrective event may be sent to thevehicle control computer 317. Vehicle control computer 317 may thenforward the blind corner corrective event to the computing device thatcontrols the seat belt tension (not shown).

Additionally, or alternatively, the blind corner corrective event mayinclude an automatic braking (i.e. deceleration) of the vehicle. Thatis, a control event that causes the speed of a vehicle to decrease viabraking may be transmitted to a computing device of a vehicle (such asvehicle control computer 317). The vehicle control computer 317 may thenforward the control event to device that controls the automatic brakingof the vehicle. The amount of braking force to be applied (or, putdifferently, the amount of deceleration to be achieved) may be adjustedprior to transmitting the control event. Alternatively, the adjustmentmay be performed by the vehicle control computer 317.

Additionally, or alternatively, the blind corner corrective event mayinclude flashing the vehicle lights as the vehicle approaches the blindcorner to alert other vehicles that might be at the blind corner.Additionally, or alternatively, the blind corner corrective event mightinclude transmitting a signal as the vehicle approaches the blind cornerto indicate the vehicle's oncoming arrival. The signal may be receivedby a second vehicle near the blind corner, e.g., to alert the driver ofthe second vehicle not to enter the path of the oncoming vehicle. Thesignal may also be received by a traffic control device (e.g., trafficlight, warning sign) which may then instruct another vehicle not toenter the roadway due to the vehicle approaching the blind corner.

The extent of the danger a blind corner poses may depend on the distancebetween the location of the intersection/curve and the point at whichthe intersection/curve becomes visible along the route of travel. Forexample, due to the reaction time of a driver, a first blind cornerhaving a relatively smaller distance between the intersection/curve andthe visibility point may be relatively more dangerous than a secondblind corner having a relatively larger distance between theintersection/curve and the visibility point. In addition, differentdrivers may have different reaction times. As a result, the same blindcorner may pose different levels of danger depending on the respectivereaction times of drivers traveling along that route. For example, ablind corner may be relatively more dangerous to a driver having arelatively slower reaction time and relatively less dangerous to adriver having a relatively quicker reaction time. Accordingly, in onearrangement, driver profile data may be retrieved from data store 204,206 and used as the basis for adjusting the control event. Driverprofile data may include the driver's age, a quality of the driver'seye-sight, estimated reaction time, routes commonly driven by thedriver, the number of blind corners on the driver's common routes, etc.The speed of the vehicle may thus be adjusted based on one or morecharacteristics from the driver's profile. For example, for younger,inexperienced drivers, the speed may be reduced by a relatively highvalue, whereas for older, experienced drivers, the speed may be reducedby a relatively low value. In another example, the speed reduction for afirst driver having a first reaction time may be less than the speedreduction for a second driver having a second reaction time that isslower than the first reaction time. In another example, the speedreduction for a first driver that commonly drives routes that havemultiple blind corners may be less than the speed reduction for a seconddriver that commonly drives routes that have little or no blind corners.Additionally, or alternatively, characteristics of the vehicle, such asthe type of the vehicle (truck-trailer, truck-semitrailer, minivan,motorbike) and the weight of the vehicle, may be used to adjust how muchthe speed of the vehicle is reduced

Additionally, or alternatively, environmental data from the predefinednavigational data received at step 400 may be used to adjust how muchthe speed of the vehicle is reduced. As noted above, the predefinednavigational data may include data about the physical attributes of theroad (e.g., slope, pitch, surface type, grade, number of lanes, trafficsignals and signs and the like), the presence of other physicalattributes of the road (e.g., pothole(s), a slit(s), an oil slick(s), aspeed bump(s), an elevation(s) or unevenness, and the like), thephysical conditions of the road (e.g., flooded, wet, slick, icy, plowed,not plowed/snow covered, etc.), population density, condition of road(e.g., new, worn, severely damaged with sink-holes, severely damaged byerosion, gravel, dirt, paved, etc.), locations of various landmarks thatare commonly found near roadways (traffic lights, traffic signs, streetsigns, safety barriers, traffic barricades, safety barriers, etc.), andlighting. Any one or combination of these characteristics may be used todetermine the amount of brake force (or speed reduction) that is to beapplied to the vehicle. For example, a greater force may be applied tothe brakes if the upcoming blind corner is on a wet road than if theupcoming blind corner is on a dry road. In another example, a greaterforce may be applied to the brakes if there is a high traffic volume onthe roads proximate to the upcoming blind corner than if there is a lowtraffic volume on the roads proximate to the upcoming blind corner. Inanother example, a greater force may be applied to the brakes if thereare a high number of street lights proximate to the upcoming blindcorner than if there are a low number of street lights proximate to theupcoming blind corner.

Additionally, or alternatively, vehicle data may be retrieved from datastore 204, 206 and used as the basis for adjusting the control event.That is, data specific to the vehicle that is approaching the upcomingblind corner may be retrieved and used to adjust the control event.Vehicle data may include the size of the vehicle, the braking distanceof the vehicle, the stopping distance of the vehicle, and the like. Anyone or combination of these characteristics may be used to determine theamount of brake force that is to be applied to the vehicle. For example,a greater force may be applied to the brakes of a first vehicle with afirst stopping distance than to a second vehicle with a second stoppingdistance that is shorter than the first stopping distance.

A different threshold value may be assigned to each of the audio,visual, and/or tactile blind corner warnings and/or the blind cornercorrective events described above. That is, as discussed above, thesewarnings and/or corrective events may be triggered if the blind cornernavigational score is above a first threshold. The determination ofwhich of the above-described audio, visual, and/or tactile blind cornerwarnings and/or the blind corner corrective events to trigger may bebased on comparing the blind corner navigational score to differentthresholds that may be assigned to each potential blind corner warningand blind corner corrective event. For example, if the blind cornernavigational score is above a second threshold, a first audio blindcorner warning may be triggered. Additionally, or alternatively, if theblind corner navigational score is above a third threshold, a firstvisual blind corner warning may be triggered. Additionally, oralternatively, if the blind corner navigational score is above a fourththreshold, a first tactile warning may be triggered. Additionally, oralternatively, if the blind corner navigational score is above a fourththreshold, a first blind corner corrective action may be triggered. Thefirst, second, third, and fourth threshold may different values or mayshare common values. These thresholds may be predefined by the driver ofthe vehicle, or may be set by the entity that maintains the blind cornernavigation system 300. Once the warning signals and/or vehicular controlevent signals are transmitted to the vehicle, processing may return tostep 402.

As discussed above, the illustrated method may be performed at regulartime intervals (i.e. every 0.5 seconds, every second, every n seconds,etc.). Therefore, a first few iterations of the method performed when avehicle is relatively far from a blind corner may result in no warningsignals or vehicular control events being transmitted to the vehicle(i.e. the blind corner navigational score may not be above thethreshold) as the blind corner and/or proximate landmarks may not bevisible from the vantage point of the vehicle. However, successiveiterations performed as the vehicle approaches the blind corner (i.e. asthe vehicle becomes relatively close to the blind corner) may result inwarning signals and/or vehicular control events being transmitted to thevehicle as the blind corner and/or proximate landmarks become visiblefrom the vantage point of the vehicle. In addition, the duration betweeniterations may shorten as the vehicle approaches the blind corner. Byway of example, when the current distance between a vehicle and anupcoming intersection or curve is between 2000 and 1000 feet, the methodmay be performed every second in order to determine whether thatintersection or curve is visible. Between 1000 and 500 feet, the methodmay be performed every half-second to determine whether the intersectionor curve is visible. After 500 feet, the method may be performed everyone-tenth of a second to determine whether the intersection or curve isvisible.

The warning signal or control event may be transmitted when the vehicleis within a threshold distance of the intersection or curve. Thethreshold distance at which the warning or control event is transmittedmay depend on various factors as described herein including, e.g., theweight of the vehicle and any corresponding load, the speed of thevehicle, the reaction time of the driver, environmental conditions, andother factors which will be appreciated with the benefit of thisdisclosure. In some instances, the warning signal or control event maybe suppressed if it is determined the driver has begun to slow thevehicle during the approach to the intersection or curve. In otherinstances, the warning signal or control event may be transmitted evenif the driver has begun to slow the vehicle during the approach to theintersection or curve.

For example, turning to FIG. 5B, a first iteration of the illustratedmethod may be performed when a vehicle is at position 560 a whiletraveling on road 590. Road 590 may be curved and a blind corner 580 maybe obscured by the curvature of road 590 and trees 575. Processing ofpredefined navigational data may indicate that trees 570 (i.e. alandmark) are within a predefined distance of blind corner 580. One ormore digital images may be received from the vehicle when it is atposition 560 a. As discussed above, processing of digital images mayinclude determining if landmarks within a predefined distance of a blindcorner are visible within the received digital images. If only aminiscule portion of the landmarks are visible within the digitalimages, a first set of warnings and/or vehicular control events may betriggered. If a relatively large portion of the landmarks are visiblewithin the digital images, a second set of warnings and/or vehicularcontrol events may be triggered. The second set of warnings and/orvehicular control events may be more severe or aggressive than the firstset, because as bigger portions of the landmarks become visible withinthe digital images, the vehicle is likely to be getting closer to theblind corner. Additionally, processing of the digital images may includedetermining whether the upcoming blind corner is visible within thedigital images. If the upcoming blind corner is visible, a relativelyhigh blind corner navigational score may be assigned, as the vehicle isrelatively close to the blind corner and the driver may need to bewarned.

Processing of the digital images received from the vehicle when it is atposition 560 a may indicate that no portion of the trees 570 nor blindcorner 580 are visible in the received digital images, thus indicatingthat blind corner 580 is not within the vantage point of the vehicle atposition 560 a. That is, the vehicle, at position 560 a, is stillrelatively far from the blind corner and the driver may not yet need tobe warning of upcoming blind corner 580. Therefore, the blind cornernavigational score may be assigned a relatively low value. Accordingly,the blind corner navigational score calculated for the vehicle when itis at position 560 a may be below the threshold, and no warning signalsor vehicular control event signals may be transmitted to the vehicle.

During a second iteration of the illustrated method, the vehicle may beat position 560 b. One or more digital images may be received from thevehicle when it is at position 560 b. Processing of the received digitalimages may indicate that a portion of the trees 570 (but not blindcorner 580) is now visible in the images, thus indicating that whileblind corner 580 is not within the vantage point of the vehicle atposition 560 b, the vehicle is relatively close to blind corner 580.Accordingly, a relatively high blind corner navigational score may becalculated for the vehicle when it is at position 560 b. The blindcorner navigational score may be above the threshold and a first set ofactions may be taken. Only a small portion of the trees 570 may bevisible in digital images received from the vehicle when it is atposition 560 b, so the first set of actions may be less severe than if alarger portion of trees 570 were visible. For example, the first set ofactions may include the transmittal of an audio warning signal but novehicular control event signals.

During a third iteration of the illustrated method, the vehicle may beat position 560 c. One or more digital images may be received from thevehicle when it is at position 560 c. Processing of the received digitalimages may indicate that a portion of the trees 570 is now visible inthe images, thus indicating that while blind corner 580 is not withinthe vantage point of the vehicle at position 560 c, the vehicle isrelatively close to blind corner 580. Accordingly, a relatively highblind corner navigational score may be calculated for the vehicle whenit is at position 560 c. The blind corner navigational score may beabove the threshold and a second set of actions may be taken. Arelatively large portion of the trees 570 may be visible in digitalimages received from the vehicle when it is at position 560 c, so thesecond set of actions may be more severe than the first set. Forexample, the first set of actions may include the transmittal of both avideo warning signal and one or more vehicular control events.

During a fourth iteration of the illustrated method, the vehicle may beat position 560 d. One or more digital images may be received from thevehicle when it is at position 560 d. Processing of the received digitalimages may indicate that the trees 570 are no longer visible in theimages but that blind corner 580 is visible in the images, thusindicating that blind corner 580 is within the vantage point of thevehicle at position 560 d. Because the blind corner 580 is within thevantage point of the vehicle at position 560 d, the vehicle isrelatively close to the upcoming blind corner 580. Accordingly, arelatively high blind corner navigational score may be calculated forthe vehicle when it is at position 560 d. The blind corner navigationalscore may be above the threshold, and a third set of actions may betaken. Because the blind corner 580 is visible in the digital images,the third set of actions may be aggressive so as to warn the driver asquickly and effectively as possible. The third set of actions mayinclude multiple warning signals (for example, both a video warningsignal and a haptic warning signal) and multiple vehicular controlevents (for example, both a pre-tensioning of the seat belt and anautomatic deceleration of the vehicle).

In an alternative implementation, the blind corner navigation system mayidentify the current location of the vehicle and determine the route avehicle is traveling. The blind corner navigation system may determinethe route, for example, based on a predefined route selected by thedriver or the vehicle. The blind corner navigation system mayadditionally or alternatively determine the route by comparing a currentgeographic location of the vehicle and compare that location to storedmap data. The blind corner navigation system may retrieve map datacorresponding to the road segments along and near the route the vehicleis traveling on. The blind corner navigation system may then analyze themap data to identify intersections and curves along the route that mightconstitute blind corners for the driver and/or the vehicle. The blindcorner navigation system may then, for each potential blind corneridentified, calculate a location along the route at which the potentialblind corner should be visible to the driver and/or the vehicle. As thevehicle travels along the route, the blind corner navigation system mayiteratively compare the current location of the vehicle to the locationsat which the identified intersections or curves should be visible. Whenthe vehicle approaches and/or arrives at a location at which an upcomingintersection or curve should be visible, the blind corner navigationsystem may determine whether that intersection or curve is, in fact,visible to the driver and/or the vehicle. The blind corner navigationsystem may then carry out one or more of the various actions describedabove (e.g., a warning, a control event) depending on whether theupcoming intersection or curve is determined to be visible.

FIG. 6 is a flow chart illustrating one example of evaluating apre-planned route for blind corner hazards according to one or moreaspects described herein. The steps shown in the flow chart may beexecuted on one or more of vehicle control computer 317, personal mobiledevice 330, blind corner navigation system 200, or blind cornernavigation server 350. In step 600, a preliminary pre-planned route maybe received. The preliminary pre-planned route may be a route that avehicle is currently traveling on, or a route that a vehicle is planningon traveling on. At step 602, blind corner navigational analysis may beperformed for the preliminary route. Performing blind cornernavigational analysis may include retrieving predefined navigationaldata for the preliminary route. As discussed above with reference toFIG. 4, predefined navigational data for the route may include roadinformation for the roads that are a part of the preliminary route. Aswith step 400, predefined navigational data may include data about thephysical attributes of the road (e.g., slope, pitch, surface type,grade, number of lanes, traffic signals and signs and the like), thepresence of other physical attributes of the road (e.g., pothole(s), aslit(s), an oil slick(s), a speed bump(s), an elevation(s) orunevenness, and the like), the physical conditions of the road (e.g.,flooded, wet, slick, icy, plowed, not plowed/snow covered, etc.),population density, condition of road (e.g., new, worn, severely damagedwith sink-holes, severely damaged by erosion, gravel, dirt, paved,etc.), locations of various landmarks that are commonly found nearroadways (traffic lights, traffic signs, street signs, safety barriers,traffic barricades, safety barriers, etc.), accident data, and lighting.The predefined navigational data may then be analyzed to identify theblind corners in the preliminary route.

In step 604, a blind corner navigational score may be calculated for thepreliminary route. Calculation of the blind corner navigational scoremay include analyzing the level of curvature of each blind corner. Asdiscussed above in reference to FIG. 4, in one arrangement, thecurvature may be identified using categorical descriptions, such as“gentle corner,” “blind corner,” “gentle curve,” and/or “blind curve.”Each categorical description may be assigned with a score. Calculationof the blind corner navigational score may include assigning a score toeach blind corner in the preliminary route based on the categoricaldescription of that blind corner, and then summing the individual scoresfor each blind corner to generate a blind corner navigational score. Theblind corner navigational score may then be adjusted based on one ormore additional factors, such as the number of blind corners in thepreliminary route.

As further discussed above in reference to FIG. 4, in a secondarrangement, the curvature may be identified using numerical valueindicating a measured curvature (i.e. information identifying that aroad segment has a curvature of 6 degrees). In this second arrangement,calculation of the blind corner navigational score may include assigninga score to each blind corner in the preliminary route based on thenumerical curvature of that blind corner. The individual scores assignedto each blind corner may then be summed to generate the blind cornernavigational score. The blind corner navigational score may then beadjusted based on one or more additional factors, such as the number ofblind corners in the preliminary route.

In one arrangement, the pre-planned route and the blind cornernavigational score may be transmitted to one or more servers associatedwith an insurance company. One or more computing devices may analyze thepre-planned route and the blind corner navigational score to evaluatethe hazard level associated with the pre-planned route or with one ormore road segments that are part of the pre-planned route. The insurancecompany may then set insurance rates for the pre-planned route or withone or more road segments that are part of the pre-planned route basedon the blind corner navigational score and the hazard levels.

In step 606, it may be determined if the blind corner navigational scoreis above a threshold value. The threshold value may be predefined, butmay additionally be dynamically modified based on the predefinednavigational data retrieved at step 602. The predefined threshold may beinitially determined based on one or more factors, such as geographicallocation of the vehicle, and/or a driving profile of the driver of thevehicle. The driving profile may include one or more drivingcharacteristics, such as reaction time (i.e. stop time), average speed,average acceleration/deceleration, previous reaction times to blindcurves, etc. Dynamic modification of the predefined threshold value maybe based on the predefined navigational data retrieved at step 602. Forexample, where the predefined navigational data indicates that thecondition of the roads in the preliminary segment and/or the roadsegment on which the blind corner is detected is hazardous (i.e. theroad is flooded, wet, slick, icy, not plowed/snow covered, has a highspeed limit, is experiencing high traffic volume, has a high accidentrate, etc.), a first predefined value/threshold may be used.Accordingly, where the predefined navigational data indicates that thecondition of the roads in the preliminary segment and/or the roadsegment on which the blind corner is detected is safe (i.e. the road isdry, even, has a low speed limit, has a low accident rate, isexperiencing low traffic volume, etc.) a second predefinedvalue/threshold may be used. The first predefined threshold may be lowerthan the second predefined threshold.

If, at step 606, it is determined that the blind corner navigationalscore is not greater than the threshold, the process may end at step608. That is, if the blind corner navigational score for the preliminaryroute is lower than the threshold, the preliminary route may deemed tobe safe, and thus no further processing is needed. If, at step 606, itis determined that the blind corner navigational score for thepreliminary route is greater than the threshold, one or more alternateroutes may be calculated at step 610. The alternate routes may have beendetermined to be safer than the preliminary route. In one arrangement,the alternate routes may have a lower blind corner navigational scorethan the preliminary route. At step 612, the one or more alternateroutes may be output to a user. The alternate routes may be transmittedto a mobile device associated with the user, such as personal mobiledevice 330, or to a vehicle associated with the user, such as vehicle310, or a navigational device associated with the user (not shown).

FIGS. 7A and 7B illustrate example user interfaces that may be displayedto a user to communicate a blind corner navigational score and/orrecommended alternate routes according to one or more aspects describedherein. FIG. 7A illustrates one example user interface 700 a thatprovides a notification to a user that the driver is approaching anupcoming blind corner. The notification may further include the blindcorner navigational score that is calculated for the upcoming blindcorner. The interface may be provided to a user on a mobile device ofthe user, on-board vehicle computing device, or other device.

In some examples, the interface 700 a may include an “OK” option whichmay clear the notification. The interface may also include an option todisplay alternative routes. Selection of “Show Alternatives” option mayprompt display of interface 700 b shown in FIG. 7B. Display of interface700 b may alternatively or additionally be prompted by the entering of apreliminary route that has a blind corner navigational score above apredefined threshold. The interface 700 b provides one or more alternateroutes that may avoid the upcoming blind corner or the predefinedpreliminary route. A user may select one or more of the alternativeroutes provided, as desired. The user may then select “Navigate” optionto enable a navigation system to provide instructions to use thealternate route. Otherwise, a user may select to cancel the alternativesprovided. The user interface may further display the difference inhazard-levels between the alternate routes (and the preliminary route,if applicable) and permit the driver to select the preferred route. Inone arrangement, a driver/vehicle may be provided a monetary benefit(e.g., a credit towards a future insurance policy) for selecting a lesshazardous route.

While the aspects described herein have been discussed with respect tospecific examples including various modes of carrying out aspects of thedisclosure, those skilled in the art will appreciate that there arenumerous variations and permutations of the above described systems andtechniques that fall within the spirit and scope of the invention.

What is claimed is:
 1. A blind corner navigation system, comprising: atleast one processor; and at least one memory storing computer-executableinstructions that, when executed by the at least one processor, causethe blind corner navigation system to: receive a preliminary route froma mobile device; receive navigational data from a map database system;process the preliminary route and the navigational data to identify oneor more blind corners of the preliminary route; process the navigationaldata and the one or more blind corners to determine a blind cornernavigational score for the preliminary route; compare the blind cornernavigational score to a threshold; based on a result of the comparing,generate an alternative route; and transmit the alternative route to themobile device.
 2. The blind corner navigation system of claim 1, the atleast one memory storing computer-executable instructions that, whenexecuted by the at least one processor, cause the blind cornernavigation system to: adjust the blind corner navigational score basedon number of blind corners in the preliminary route.
 3. The blind cornernavigation system of claim 1, wherein the navigational data comprisesroad information for one or more roads that are a part of thepreliminary route.
 4. The blind corner navigation system of claim 3,wherein the navigational data includes information indicative of alocation of a landmark.
 5. The blind corner navigation system of claim1, wherein the processing the navigational data and the one or moreblind corners to determine the blind corner navigational score for thepreliminary route comprises analyzing a level of curvature of each blindcorner of the one or more blind corners.
 6. The blind corner navigationsystem of claim 5, wherein the processing the navigational data and theone or more blind corners to determine the blind corner navigationalscore for the preliminary route further comprises assigning a score toeach blind corner of the one or more blind corners based on the level ofcurvature of that blind corner.
 7. The blind corner navigation system ofclaim 6, wherein the processing the navigational data and the one ormore blind corners to determine the blind corner navigational score forthe preliminary route further comprises summing the score assigned toeach blind corner of the one or more blind corners.
 8. The blind cornernavigational system of claim 1, wherein the threshold is initiallydetermined based on a driving profile of a driver of a vehicle and isdynamically modified based on weather conditions.
 9. The blind cornernavigational system of claim 1, wherein the threshold is dynamicallymodified based on a condition of a road on which a first blind corner ofthe one or more blind corners is located.
 10. A non-transitory computerreadable medium storing instructions that, when executed by one or moreprocessors, cause the one or more processors to: receive a preliminaryroute from a mobile device; receive navigational data from a mapdatabase system; process the preliminary route and the navigational datato identify one or more blind corners of the preliminary route; processthe navigational data and the one or more blind corners to determine ablind corner navigational score for the preliminary route; compare theblind corner navigational score to a threshold; based on a result of thecomparing, generate an alternative route; and transmit the alternativeroute to the mobile device.
 11. The non-transitory computer readablemedium of claim 10, storing instructions that, when executed by one ormore processors, cause the one or more processors to: adjust the blindcorner navigational score based on number of blind corners in thepreliminary route.
 12. The non-transitory computer readable medium ofclaim 10, wherein the navigational data comprises road information forone or more roads that are a part of the preliminary route.
 13. Thenon-transitory computer readable medium of claim 12, wherein thenavigational data includes information indicative of a location of alandmark.
 14. The non-transitory computer readable medium of claim 10,wherein the processing the navigational data and the one or more blindcorners to determine the blind corner navigational score for thepreliminary route comprises analyzing a level of curvature of each blindcorner of the one or more blind corners.
 15. The non-transitory computerreadable medium of claim 14, wherein the threshold is initiallydetermined based on a driving profile of a driver of a vehicle and isdynamically modified based on weather conditions.
 16. A methodcomprising: receiving a preliminary route from a mobile device;receiving navigational data from a map database system; processing thepreliminary route and the navigational data to identify one or moreblind corners of the preliminary route; processing the navigational dataand the one or more blind corners to determine a blind cornernavigational score for the preliminary route; comparing the blind cornernavigational score to a threshold; based on a result of the comparing,generating an alternative route; and transmitting the alternative routeto the mobile device.
 17. The method of claim 16, further comprising:adjusting the blind corner navigational score based on number of blindcorners in the preliminary route.
 18. The method of claim 16, whereinthe navigational data comprises road information for one or more roadsthat are a part of the preliminary route.
 19. The method of claim 18,wherein the navigational data includes information indicative of alocation of a landmark.
 20. The method of claim 16, wherein theprocessing the navigational data and the one or more blind corners todetermine the blind corner navigational score for the preliminary routecomprises analyzing a level of curvature of each blind corner of the oneor more blind corners.